Abstract [en]

This degree project evaluates combinations of well-known state-of-the-art keypoint detectors and descriptors, as well as keypoint matching and robust outlier rejection methods for the purpose of estimating a homography between images produced by two fundamentally different cameras. The evaluation is perfomed on both computational efficiency and matching accuracy of each combination after a series of image deformations have been applied. The results show best performance using Brute Force search with the Hamming distance on keypoint descriptors generated by running the BRISK/BRISK combination and RANSAC for finding the subset to be used in the final homography estimation. If necessary for extra time sensitive applications, using ORB/ORB for keypoint detection and description has been shown to produce largely comparable results at a higher computational efficiency